Bassignana Final UGB Blog

Urban Growth Boundaries: What do the policy implications look like?

-By: Paola Bassignana

Introduction

An Urban Growth Boundary (UGB) is an “officially adopted and mapped line that separates an urban area from its surrounding greenbelt of open lands, including farms, watersheds and parks. UGBs are set for significant periods of time — typically 20 years or more — to discourage speculation at the suburban fringe,” (Greenbelt.org). UGB’s are cited to serve as a planning policy to increase population and development density, which also increases land-use efficiency, increased use of public transit and promotes innovation and economic growth. It is also said that implementation of a UGB reduces per capita resource use and results in lower negative environmental impact. However, according to groups opposing UGBs, these policies also carry negative, regressive effects that primarily affect low-income communities. The primary of these are its effects on housing prices; opposition to UGBs assert that this policy increase housing prices within the boundaries, forcing low-income families out of the city and into the less developed, less desirable, and underserved areas outside of the boundary. Probably the most popular UGB is that of Portland, Oregon. Portland is often considered an ideal city by many planners because of its balance between the built environment and green space among other things. Established in 1973, the Portland UGB is often linked with this city’s successes (PortlandMetro).

In this project, I sought to spatially describe the effects of the UGB policy on Portland by mapping out demographic factors, transit ridership patterns, and median home values. To asses if these factors could be a result of the UGB, I compared the aforementioned factors in the Portland Metro Area to those of the Denver, Colorado Metro Area because it does not have a UGB. I chose Denver as a comparable city because of their similar size, population, and demographic features.

Areas of Study: Portland, OR & Denver, CO

Area of Study:

The above map shows the two areas of study: The Portland Metro Area, and the Denver Metro Area. The Portland Metro Area covers seven counties, five of which are in Oregon, and two belonging to the state of Washington. The Denver Metro Area includes 10 counties, all of which are within the state of Colorado.

Population: Portland Metro Area

Comparison of Population Concentrations

The above map features the Portland Metro Area in grey with the Portland city center symbolized by a bird. The UGB on the inside is noted by a violet boundary. The bright blue points signify people, with each dot representing 500 people. The map shows that the densest area in the Portland Metro Area is, in fact, the inside the UGB. However, it is interesting to note there exists a second area with a dense concentration of people to the top right, outside of the boundary.

Population: Denver, CO

The above map features the Denver Metro Area in green with the Denver city center symbolized by a triangle. The blue points signify people, with each dot representing 500 people. This map shows that a vast majority of the population is concentrated in and around close proximity to the city center, despite not having a UGB. The population density seems to have a more even distribution than that of Portland, which is interesting considering the fact that the UGB is meant to encourage this kind of population distribution.

Commuter Breakdowns

Since the literature on UGBs suggests that commuter patters shift from single rider car dependency to alternative means of transportation, the following maps are a visual of commuter patterns within both metro areas.

Commute Modes: Portland Metro Area

In the above map of the Portland Metro Area, the population by census tract is noted by the graduated teal color. The commute modes are represented by colored dots, each dot representing 200 people, with each color representing a different commute mode: blue= single driver, green= carpool, tan= public transit, turquoise= bike, and purple= walk. According to this map, a large majority of Portland commuters are single drivers, leaving only about 24% who use alternative transportation.

Commute Modes: Denver Metro Area

In the above map of the Denver Metro Area, the population by census tract is noted by the graduated orange color. The commute modes are represented by colored dots, each dot representing 200 people, with each color representing a different commute mode: purple= single driver, green= carpool, turquoise= public transit, tan= bike, and blue= walk. Single drivers make up a vast majority of commuters in Denver, with only about 17% using alternative means of travel to work.

By comparing these two maps, it shows that alternative commute modes to work are used more often in Portland by about seven percentage points. Though not necessarily a huge number, this difference is significant.

Average Home Values

The following maps show the median home values in both Metro Areas first, by census tract. The average home values are then calculated within buffers originating from the city center at five, 10, 25, and 50 mile radii.

Portland Metro Area Home Values by Census Tract

Portland Home Values: Within Distances from City Center

As the map shows, high home value zones are scattered throughout the Portland Metro Area. When the buffers are added and the average home values are then calculated within those buffers, it shows a steady decline in value from the center, out. These maps could provide visuals that support the claim that the UBG makes housing more expensive, as the two most valued property averages are located within it. Further investigation would need to be done in order to confirm the causality between high home values and the UGB.

Denver Home Values by Census Tract

Denver Home Values: Within Distances from City Center

As the map shows, high home value zones are concentrated in two major areas: the city center and what is presumably a, suburban area within the Denver Metro Area. When the buffers are added and the average home values are then calculated within those buffers, it shows a less obvious pattern in value than the map of Portland shows.

Findings and Conclusion:

By mapping out population distribution, commute modes, and average housing values and comparing an area with an UGB to that of an area that does not, interesting characteristics of the two are revealed. From this basic analysis, it can be said that the predicted effects of the UGB did occur, but the magnitude of the changes are perhaps not as great as predicted. In this project, it can be seen that the population distribution of Portland does not quite follow what the UGB aims to encourage—high density in a central area. It does have a large concentration of people around the city center, but there appears to also be a large concentration on one edge of the UGB border. It would be interesting to further investigate the characteristics of this population. That second concentration raises the question that perhaps this maybe where the low-income families that cannot afford inner UGB life move to if the claim made by opponents to the UGB are correct. The Portland Metro area does have a larger commuter share than uses alternative forms of transportation to work other than a single driver car in comparison Denver. The difference however, is only by about seven percentage points. Home values within the UGB are also higher than that of Denver, which does not have a UGB.

Denver also has more expensive homes near the city center, but the areas of high home costs have a different pattern than those of Portland.

GIS could be a valuable tool, coupled with other investigative measures, in completing a thorough study of the UGB in Portland. Additional factors important to consider adding to this analysis would be the median age of residents, housing tenure and race/ethnicity. Including the same maps of the same areas, but including 1970 (pre-UGB) data would also help link the effects to the UGB.

Complications

All demographic data for this project was collected using The Census American Fact Finder. Some major data joining complications severely limited the amount of analysis I was actually able to complete. Many of the joins required creative manipulations to the data tables in order to work in its most basic form.

 Methodologies

Since the spatial analyst function refused to work, median home values within specific mileage ranges were calculated using buffers and extracting data (average median value) from within those buffers.

Creating the Metro Areas shape files was done by collecting census data for all counties within the metro area, joining it to the state file, and doing a select by attributes [GEOid3 IS NOT =NULL]. That data was then exported as a new shape file and layer.

Skills Used:

1)    Modeling

2)    Measurement

3)    Original data

4)    Custom Shapefile

5)    Geoprocessing (dissolve, clip)

6)    Buffering

7)    Aggregating attribute fields

8)    Charts

9)    Boundary subset selections (Portland UGB)

10) Attribute selection

Model Used:

Due to data complications, more complex models were not able to be used.

Sample Model Used

Sources:

“Metro: Urban growth boundary.” Metro: Welcome to Metro. Portland Oregon Metro, n.d. Web. 9 Mar. 2012. <http://www.oregonmetro.gov/index.cf

Oregon.gov Geospacial Enterprise Office: Urban growth boundaries

UCLA Map Share: Major US Cities, US shapefile

“Urban Growth Boundaries.” Greenbelt.org. N.p., n.d. Web. 6 Mar. 2012. <http://www.greenbelt.org/wp-content/uploads/2012/02/ugb.pdf>.

US Census Bureau: Fact Finder: for all demographic data sets